Description and Analysis of an Indoor Positioning System That Uses Wireless ZigBee Technology

Introduction

The positioning systems arose years ago with the aim of being able at any moment to know the situation of mobile objects and being able to realize their pursuit. Those systems were very complex and expensive at the time because they required the newest technology of the time and therefore they were not accessible for the great majority of the people and organizations. Nowadays, and due to the development of the technologies and the electronics, these systems have evolved a lot and are used daily in multiple sectors of the society (such as auto motion, industrial automatism or people pursuit). This height in telecommunications and this type of applications has been translated in multitude of location, positioning and pursuit systems, with diverse technologies associated, generating a wide range of possibilities.

At the moment, there is a group of positioning systems very interesting. They can locate in interiors using radio frequency signals. In order to reach the objective of the location Bluetooth (Labiod et al., 2007), WLAN (Labiod et al., 2007), ZigBee (ZigBee Standards Organization, 2008; Labiod et al., 2007) or RFID technology (Ni et al., 2003) can be used. For such aim, Chipcon Company (now absorbed by Texas Instruments) commercialized the chip CC2431 that, besides being a ZigBee transceiver, included a microprocessor of 8051 family and a hardware location engine (Aamodt, 2006). With those chips, a wireless location system can be mounted in interiors (although also it is valid for mixed exteriors or surroundings) based on radio signals, and more concretely, in the study of the received signals strength. With these measures, an estimation of the position of mobile devices can be estimated with the help of several perfectly located nodes which work as a reference.

They are the methods to carry this estimation out based on the received signal strength. One of them, the simplest one, consists of making a map with the signal powers that would arrive at a group of located receivers. They cover the surface where it is the location is needed, with a certain overlapping. Thus, comparing the received signal levels from the mobile devices with the measures previously stored, the position can be estimated.

Bahl et al., presented in March of 2000 a work called `RADAR: An In-Building RF-based User Location and Tracking System', in which RADAR system is described (Bahl et al., 2000). As indicated in the title, RADAR is a location system based on radio frequency whose purpose is the location and pursuit of objects or movable people in interiors. RADAR is based on the engraving and processing of the information of signal power of the system in different stations located in strategic positions. These radio stations covered the area where the system was working with some overlapping to be able to provide more trustworthy and precise results. The measured data from previous experimentation with a propagation model for the signal are combined to determine the position of the object or subject to locate.

The second method consists of placing the fixed receivers and eliminating the previous measures to be stored in the data base. These fixed receivers, or a central node, take the level from the signal received from the mobile device and based in a model of attenuation of the signal (or following another algorithm) they will compute the distance between every fixed node and a moving body, being possible to make a location.

In 2006 Masashi et al., published ‘Indoor Location System using RSSI measurement of Wireless sensor network based on ZigBee standard’ (Sugano et al.). As its name indicates, during this study a location system was implemented based on the measurement of the power of the received signals using wireless nodes with ZigBee technology. The implemented system sends packages that at least, include their identity to three sensorial nodes that measure the RSSI and are in a well-known position. Obtained these values, fixed nodes send the data to a central node which computes them and estimates the position of the movable nodes from these measured data.

The third method is a similar idea, but decentralizing the system. Fixed nodes send packages to movable nodes, and they receive different signal power levels from every reference node. These packages contain the real position of the reference nodes, and taking the data, movable devices are able to estimate their own positions.